Science Score: 31.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (2.6%) to scientific vocabulary
Repository
Spring 2023 PSU PHYS 496 course
Basic Info
- Host: GitHub
- Owner: prokudin
- Language: Jupyter Notebook
- Default Branch: master
- Size: 43.5 MB
Statistics
- Stars: 0
- Watchers: 4
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
PSU_PHYS496
If you are interested, please, watch this video: https://psu.mediaspace.kaltura.com/media/1_edhgzj0i
Pytorch neural network for Gluon Dataset: https://github.com/ryantuckman/Machine-Learning/blob/main/mypytorch.ipynb Tensorflow neural network for Gluon Dataset: https://github.com/ryantuckman/Machine-Learning/blob/main/tensorflowgluondataset.ipynb Example of GAN: https://github.com/ryantuckman/Machine-Learning/blob/main/v2-event-image-2D-W.ipynb More helpful resources --- python and numpy introduction: https://github.com/ryantuckman/Machine-Learning/blob/main/pythonnumpyintroduction.ipynb example pytorch notebook: https://github.com/ryantuckman/Machine-Learning/blob/main/pytorchexample.ipynb another neural network in pytorch: https://github.com/ryantuckman/Machine-Learning/blob/main/simplepytorchdeeplearningnotebook.ipynb
PyTorch tutorials: https://pytorch.org/tutorials/beginner/basics/quickstart_tutorial.html https://www.fast.ai
Owner
- Name: Alexei Prokudin
- Login: prokudin
- Kind: user
- Company: PSU Berks and JLab
- Repositories: 2
- Profile: https://github.com/prokudin
Citation (Citations/api_code.py)
import urllib.request, urllib.parse
import json
import ssl
import validators
#API Implementation
# Ignores unnecesary SSL errors
ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.verify_mode = ssl.CERT_NONE
def url_parser(url): # Returns data in json format
if not bool(validators.url(url)): raise ValueError(f'Bad URL: {url}') # URL format check
html = urllib.request.urlopen(url, context = ctx) #Handle for URL inputted
# soup = bs4.BeautifulSoup(html, 'html.parser')
data = html.read().decode()
try:
json_data = json.loads(data)
except Exception as e:
json_data = None
print(e)
return json_data
#Will be done by wednsday
def url_construct(api_url: str, url_elements: dict, identifiers: list, search: bool): # Constructs URL to get search query or obtain record
parameters = {}
if search:
for key, value in url_elements.items():
parameters[key] = value
extension = '?' + urllib.parse.urlencode(parameters)
else:
extension = ''
url = api_url + extension
return url
api_url = 'https://inspirehep.net/api/'
internal_identifiers = ['literature', 'authors', 'institutions', 'conferences', 'seminars', 'journals', 'jobs', 'experiments', 'data']
external_identifiers = ['doi', 'arxiv', 'orcid']
# import re
# test = None
# # refactoring of code above
# citation_list = re.findall('\{(.+)*\,(.+)*\,(.+)*\}', test)
# citation_list
url_parser(url_construct({}))